The optimal design of training sequences for channel estimation in multiple-input multiple-output （MIMO） systems under spatially correlated fading is considered. The channel is assumed to be a block-fading model wit...The optimal design of training sequences for channel estimation in multiple-input multiple-output （MIMO） systems under spatially correlated fading is considered. The channel is assumed to be a block-fading model with spatial correlation known at both the transmitter and the receiver. To minimize the channel estimation error, optimal training sequences are designed to exploit full information of the spatial correlation under the criterion of minimum mean square error （MMSE）. It is investigated that the spatial correlation is helpful to decrease the estimation error and the proposed training sequences have good performance via simulations.展开更多
Although the Cramer-Rao Bound(CRB) can be used as the benchmark of estimation algorithm performance,it's too complicated for joint training sequence(TS) design for multiple input multiple output(MIMO) orthogonal f...Although the Cramer-Rao Bound(CRB) can be used as the benchmark of estimation algorithm performance,it's too complicated for joint training sequence(TS) design for multiple input multiple output(MIMO) orthogonal frequency division multiplexing(OFDM) coordination on multiple point(CoMP) systems.So a minimum mean square error(MSE) based sub-optimal sequence design criterion was proposed,including ideal sequence correlation property and sequence length constraint.The simulation results verify the theory analysis.展开更多
In the current research on intensity-modulation and direct-detection optical orthogonal frequency division multiplexing(IMDD-OOFDM) system, effective channel compensation is a key factor to improve system performance....In the current research on intensity-modulation and direct-detection optical orthogonal frequency division multiplexing(IMDD-OOFDM) system, effective channel compensation is a key factor to improve system performance. In order to improve the efficiency of channel compensation, a deep learning-based symbol detection algorithm is proposed in this paper for IMDD-OOFDM system. Firstly, a high-speed data streams symbol synchronization algorithm based on a training sequence is used to ensure accurate symbol synchronization. Then the traditional channel estimation and channel compensation are replaced by an echo state network(ESN) to restore the transmitted signal. Finally, we collect the data from the system experiment and calculate the signal-to-noise ratio(SNR). The analysis of the SNR optimized by the ESN proves that the ESN-based symbol detection algorithm is effective in compensating nonlinear distortion.展开更多
基金the National Science Foundation for Distinguished Young Scholars (60725105)the SixthProject of the Key Project of National Nature Science Foundation of China (60496316)+2 种基金the National "863" Project (2007AA012288)the National Nature Science Foundation of China (60572146)the "111" Project (B08038).
文摘The optimal design of training sequences for channel estimation in multiple-input multiple-output （MIMO） systems under spatially correlated fading is considered. The channel is assumed to be a block-fading model with spatial correlation known at both the transmitter and the receiver. To minimize the channel estimation error, optimal training sequences are designed to exploit full information of the spatial correlation under the criterion of minimum mean square error （MMSE）. It is investigated that the spatial correlation is helpful to decrease the estimation error and the proposed training sequences have good performance via simulations.
基金International Science&Technology Cooperation Projects of Qinghai,China(Nos.2013-H-811,2014-HZ-821)Chunhui Plan Projects,China(Nos.Z2014013,Z2014014)
文摘Although the Cramer-Rao Bound(CRB) can be used as the benchmark of estimation algorithm performance,it's too complicated for joint training sequence(TS) design for multiple input multiple output(MIMO) orthogonal frequency division multiplexing(OFDM) coordination on multiple point(CoMP) systems.So a minimum mean square error(MSE) based sub-optimal sequence design criterion was proposed,including ideal sequence correlation property and sequence length constraint.The simulation results verify the theory analysis.
基金supported by the National Natural Science Foundation of China(61831003).
文摘In the current research on intensity-modulation and direct-detection optical orthogonal frequency division multiplexing(IMDD-OOFDM) system, effective channel compensation is a key factor to improve system performance. In order to improve the efficiency of channel compensation, a deep learning-based symbol detection algorithm is proposed in this paper for IMDD-OOFDM system. Firstly, a high-speed data streams symbol synchronization algorithm based on a training sequence is used to ensure accurate symbol synchronization. Then the traditional channel estimation and channel compensation are replaced by an echo state network(ESN) to restore the transmitted signal. Finally, we collect the data from the system experiment and calculate the signal-to-noise ratio(SNR). The analysis of the SNR optimized by the ESN proves that the ESN-based symbol detection algorithm is effective in compensating nonlinear distortion.
